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The geographical distribution of lymphatic filariasis infection in Malawi

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Mapping distribution of lymphatic filariasis (LF) is a prerequisite for planning national elimination programmes. Results from a nation wide mapping survey for lymphatic filariasis (LF) in Malawi are presented. Thirty-five villages were sampled from
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  BioMed   Central Page 1 of 7 (page number not for citation purposes) Filaria Journal Open Access Research The geographical distribution of lymphatic filariasis infection in Malawi BagreyMMNgwira* 1,2 , PhillimonTambala 3 , A MariaPerez 2 , CameronBowie 2  and DavidHMolyneux  1  Address: 1 Lymphatic Filariasis Support Centre, Liverpool School of Tropical Medicine, Pembroke Place, L3 5QA, UK, 2 Malawi College of Medicine, P/Bag 360, Blantyre3, Malawi and 3 Onchocerciasis Control Programme, PO Box 2273, Blantyre, MalawiEmail: BagreyMMNgwira*-bngwira@africa-online.net; PhillimonTambala-ief@malawi.net; A MariaPerez-sgraham@mlw.medcol.mw; CameronBowie-cbowie@medcol.mw; DavidHMolyneux-david.molyneux@liv.ac.uk * Corresponding author Abstract Mapping distribution of lymphatic filariasis (LF) is a prerequisite for planning national eliminationprogrammes. Results from a nation wide mapping survey for lymphatic filariasis (LF) in Malawi arepresented. Thirty-five villages were sampled from 23 districts excluding three districts (Karonga,Chikwawa and Nsanje) that had already been mapped and Likoma, an Island, where access was notpossible in the time frame of the survey. Antigenaemia prevalence [based onimmunochromatographic card tests (ICT)] ranged from 0% to 35.9%. Villages from the westernside of the country and distant from the lake tended to be of lower prevalence. The exception wasa village in Mchinji district on the Malawi-Zambia border where a prevalence of 18.2% was found.In contrast villages from lake shore districts [Salima, Mangochi, Balaka and Ntcheu (Bwanje valley)]and Phalombe had prevalences of over 20%.A national map is developed which incorporates data from surveys in Karonga, Chikwawa andNsanje districts, carried out in 2000. There is a marked decline in prevalence with increasingaltitude. Further analysis revealed a strong negative correlation (R 2 = 0.7 p < 0.001) betweenaltitude and prevalence. These results suggest that the lake shore, Phalombe plain and the lowerShire valley will be priority areas for the Malawi LF elimination programme. Implications of thesefindings as regards implementing a national LF elimination programme in Malawi are discussed. Background Lymphatic filariasis (LF) has been identified as a major public health problem and is endemic in over 80 coun-tries. It is currently estimated that up to 120 million peo-ple are infected with Wuchereria bancrofti in about 83endemic countries [1]. Of these, it is estimated 40 millionpeople have evidence of chronic manifestations such ashydrocele and lymphoedema/elephantiasis. In additionthe affected individuals suffer repeated episodes of ade-nolymphangitis ('acute attacks') which result in markedloss in their economic productivity [2]. Improved thera-pies and diagnostic methods have led to the realisationthat it should be possible to interrupt transmission andeliminate LF by repeated, annual cycles of mass drug administration (MDA), with single dose combination reg-imens [3]. Thus, in 1997 the World Health Assembly passed a resolution calling for strengthening of activitiesleading to the elimination of LF as a "public health prob- Published: 29 November 2007 Filaria Journal   2007, 6 :12doi:10.1186/1475-2883-6-12Received: 17 April 2007Accepted: 29 November 2007This article is available from: http://www.filariajournal.com/content/6/1/12© 2007 Ngwira et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the srcinal work is properly cited.  Filaria Journal   2007, 6 :12http://www.filariajournal.com/content/6/1/12Page 2 of 7 (page number not for citation purposes) lem [4]." This resulted in the initiation of the now well-established Global Program to Eliminate Lymphatic Filariasis (GPELF) in 2000.Malawi has two previously known LF foci: one in thesouthern part (Shire valley) and the other in the northernregion along the Songwe river which forms its border with Tanzania [5,6]. However there had been no detailed com-munity based surveys for LF in Malawi apart from one inthe northern focus which was conducted in 1960. Thissurvey, based on microscopic examination (for microfila-rae) of thick bloodsmears which were made from samplescollected at night, showed a high prevalence of microfila-raemia amongst adults (40%) and suggested that humaninfection with W. bancrofti  was confined to communitiesin close proximity to the Songwe River [7].More recently, surveys in these two foci have reportedhigh antigenaemia prevalence based on immunochroma-tographic (ICT) card tests that approached 80% in someof the sampled villages [8,9]. There was also a higher thanexpected prevalence of LF associated disease in both areas(4% lymphoedema and up to 18% hydrocele). In addi-tion, the survey in Karonga established that W. bancrofti infection is more wide spread than previously recognised, whereas in the lower Shire valley a markedly higher anti-genaemia prevalence (55%) was found amongst children(aged 1–9 years) than what has been reported in any of the published literature. Towards the end of 2003 we completed a nation-widemapping exercise using ICT cards. The objective was toobtain data on the geographical distribution of LF in theremaining districts in Malawi as a prerequisite to initiating national LF elimination activities. This paper presentsfindings from a 2003 survey and incorporates data fromrecent surveys in the two known foci that have already appeared in the scientific literature to produce, for the first time, a complete map of the distribution of LF infection(based on adult worm antigenaemia) in Malawi. Theimplications of this distribution for LF control pro-gramme planning and eventual implementation are dis-cussed. Methods Malawi is administratively divided into northern, centraland southern regions. These are further divided into 28districts. Two new districts (Neno – parent district –Mwanza and Likoma Island – parent district – Nkhata-Bay) were formed after this survey had already beenplanned and thus were mapped within there parent dis-tricts. In addition, access to Likoma, an Island District, was not possible in the time frame of this survey. LF prev-alence data were available for three districts; Karonga Dis-trict in the northern region, Chikwawa and NsanjeDistricts in the southern region. The latest survey did not cover these districts. In the remaining districts we aimedto sample a random selection of villages for antigen test-ing. A database of villages by district was made available via the WHO's HealthMapper software. A programmeincorporated in the software was used to provide a ran-dom sample of villages to be surveyed. The selected vil-lages had a 50 km buffer zone as recommended by the WHO's rapid assessment for the geographical distributionof lymphatic filariasis (RAGFIL) method [10]. Three addi-tional villages were chosen in the field from inhabitedareas from where the database did not contain any vil-lages. The testing protocol adopted followed recommen-dations of the RAGFIL method that is based on Lot Quality Sampling (LQAS) scheme [11]. Briefly, if at least 10 (20%) of the first 50 individuals (aged >15 years)tested were positive testing could be stopped; otherwiseup to 100 individuals were to be tested per sampling point [11]. However since many villages are sparsely populatedan adjacent village to the randomly selected one were alsoinvited to participate in order to achieve the required sam-ple size. Hence random selection of subjects was not fea-sible in most villages. Before testing could be carried out ameeting with village members was held and the objectivesof the survey were explained in the local language. Eachconsenting individual provided demographic data (ageand sex) and a finger prick blood sample. The wholeblood obtained was immediately applied onto the ICT (Binax Inc., Portland, ME) card and read within ten min-utes according to the manufacturer's instructions. If twolines appeared in the viewing window that particular indi- vidual was regarded as positive for LF [12]. Individualsfound positive were treated on the spot with albendazole(400 mg) and ivermectin (200  g/kg body weight). Allsampled villages had geo-coordinates determined by aportable Geographical Positioning System (GPS-GarmineTrex  ® ) machine. Ethics  The survey received ethical clearance from the MalawiMinistry of Health Sciences Research Committee (HSRC)and from the Liverpool School of Tropical Medicine Eth-ics Committee. Individual consent was obtained fromeach participant or (if they were aged <16) from one of their parents or a guardian. Data Management Data were entered into the computer using EPINFO 2000(CDC, Atlanta) software. The data were subsequently exported into STATA version 7 (Stata Corporation, Col-lege Station, TX) for descriptive statistical analyses. Inorder to investigate the relationship between prevalenceand altitude, log transformation of the prevalence data was carried out using the formula log  10 (x + 1). Villagegeographical coordinate data were used to produce a map  Filaria Journal   2007, 6 :12http://www.filariajournal.com/content/6/1/12Page 3 of 7 (page number not for citation purposes) showing the spatial distribution of LF infection using the WHO's HealthMapper software. Results  A total of 35 data points were sampled. Of these three were chosen in the field in inhabited areas where there were no villages on the Healthmapper database. A total of 2913 individuals were examined. The age and sex distri-bution of the survey participants is shown in Figure 1. There was a female excess (64%) amongst the study par-ticipants (more marked in the 20–24 age bracket). Overallthere were 269 (9.2%) individuals positive for circulating filarial antigen (CFA) based on ICT results. Significantly more males than females tested positive (11.0% vs 8.2%p = 0.01). Figure 2 shows the proportion of those positivefor CFA by age and sex. Amongst the males, those positive,tended to be older (student t test p = 0.08). This relation-ship was not observed in their female counterparts.Survey prevalence data by district and village are pre-sented in Table 1. This ranged from 0% to 35.9%. The spa-tial distribution of the sampled villages with their prevalence category are shown in Figure 3. In general vil-lages in the western side of the country registered a CFA prevalence of less than 10%. This is with the exception of Mzenga Village in Mchinji District along the Malawi-Zam-bia border where a prevalence of 18.2% was found. Prev-alence of over 20% was observed from villages in Salimaand Mangochi Districts along the southern shore of LakeMalawi. Also in Ntcheu district (Bwanje Valley), Balakadistrict near Lake Malombe and finally in Phalombe dis-trict along the shores of Lake Chilwa. The highest preva-lence (35.9%) was recorded at Kalembo village in Balakadistrict in southern Malawi.Prevalence data from the 2000 surveys are summarised in Table 2. The geographical distribution of data points sam-pled (ICT) in Malawi (except two villages in Nsanje Dis-trict where it was not possible to obtain geographicalcoordinates) showing prevalence in relation to altitude ispresented in Figure 4. Figure 5(a) shows a scatter plot of antigen prevalence by altitude. There is notable decline inprevalence with increasing altitude and further statisticalanalyses on log transformed prevalence data [Figure 5(b)]have shown a significant negative correlation betweenaltitude and prevalence (R  2 = 0.7 p < 0.001). Discussion  The present survey, in the remaining unmapped districtsin Malawi, has shown that infection with W. bancrofti asdetermined by antigenaemia prevalence is more wide-spread than previously appreciated. The female excessobserved amongst our survey population probably reflects the fact that males are often out in the field during the day thus not available for testing. The implication of this being that the prevalence we found in some of our sampled villages is likely to be an under-estimate of thetrue prevalence. This is due to the fact that in most com-munities significantly more males tend to carry the infec-tion as has been observed in this survey and in other surveys from Malawi and elsewhere in Africa [9,13].In all districts, except Chitipa in the north, there was at least one individual who was positive on ICT. The low prevalence found in villages from the western side of Malawi could be explained by the fact that these areas aredry, of relatively higher altitude and thus not ideal for extensive mosquito breeding. The 18.2% prevalenceobserved at Mzenga Village in Mchinji along the Zambiaborder is intriguing. This is particularly so as there havebeen no anecdotal reports of LF disease from either theMalawi or Zambia side of the border in this area. Of noteis that this village is in close proximity to a perennialstream that sustains a reasonable amount of irrigated The proportion of males and females positive for CFA by age Figure 2 The proportion of males and females positive for CFA by age.   Age group (years)    P  r  o  p  o  r   t   i  o  n   (   %   )          The age and sex distribution of survey participants Figure 1 The age and sex distribution of survey participants.  Age group (years)       N    u    m      b    e    r           Filaria Journal   2007, 6 :12http://www.filariajournal.com/content/6/1/12Page 4 of 7 (page number not for citation purposes) onion farming. Whether this setting is conducive for sup-porting extensive mosquito breeding and thus driving W.bancrofti infection as has been observed in NorthernMalawi and Ghana will need further investigation [14].Ideally this should be coupled with human night bloodexamination for microfilariae.It is also interesting to note that some villages from dis-tricts (Rumphi, Nkhata-Bay and Nkhotakota) along thelake shore had prevalence of less than 10%. A possibleexplanation could be due to the fact that these districts aremountainous and thus well drained consequently limit-ing potential mosquito breeding sites. The relatively high prevalence found in Salima, Ntcheu(Bwanje Valley), Balaka, Mangochi and Phalombe wasunexpected. However there have been isolated unpub-lished reports of cases with chronic manifestation of LF(hydrocele and elephantiasis) in these areas. It is worthnoting that the ecological conditions in these districts areideal for supporting large potential LF vector populations.Incorporating data from 2000 surveys clearly shows that the priority areas for LF control activities in Malawi will bethe lakeshore districts, Phalombe plain and the Lower Shire Valley. The decline in LF prevalence with increasing altitude hasalso been reported from other settings in Africa [15]. Thisis believed to be due to the influence of altitude on tem-perature which is known to be critical for survival of the vector and development of the parasite within the vector [16]. These findings have important implications for initiating the "Malawi LF Elimination Programme". First, following  WHO's recommendation that all implementation units Table 1: ICT antigen prevalence data from the nation wide survey conducted in 2003 DistrictVillageNumber testedNumber positivePrevalenceLatitudeLongitude BalakaKalembo531935.814.8450035.16900BlantyreMasanjala Lilangwe7756.515.5449035.02184ChiradzuluMbalame8167.415.7000035.10000ChitipaChisenga85009.9750033.38977ChitipaSiyombwe77009.6844133.24764DedzaKamenyagwaza6457.814.4075034.98750DowaChimangamsasa7245.613.7096433.99795KasunguKadyaka650013.0763333.48360KasunguKaluluma10532.912.5807733.51870LilongweMwenda 1 T/A Chadza8467.114.1407433.78825MachingaPhuteya7034.315.1900035.09887MangochiChilawe9299.813.8000035.10300MangochiChiponde901213.314.3830035.10000MangochiMtuwa822125.614.6840035.55100MchinjiChalaswa9844.114.1168933.32919MchinjiMzenga991818.213.6042732.73460MulanjeGawani7867.715.9810035.78300MulanjeMbewa691318.815.9997035.48611MwanzaChapita A6434.715.6302234.59139MzimbaMilingo-Jere1010012.2037433.33340MzimbaKambombo10221.911.1755133.52649Nkhata-BayKalumpha10476.712.0873334.05695Nkhata-BayMizimu10387.811.5582034.18150NkhotakotaMowe12211912.5549634.13366NkhotakotaTandwe8133.713.0298134.26246NtcheuGwaza922628.314.5280034.68000NtcheuNkonde-16669.114.9857034.82825NtchisiKalulu993313.3312933.74804PhalombeMaguda781924.415.5177435.78996RumphiBongololo7211.410.8127633.52233RumphiMhango8289.810.8100033.52379SalimaChipoka-Nkwizi731621.914.0367634.50614SalimaKasonda781316.713.5982834.29268ThyoloNkaombe9566.315.9927135.04998ZombaKapenda5723.515.3588535.40305  Filaria Journal   2007, 6 :12http://www.filariajournal.com/content/6/1/12Page 5 of 7 (page number not for citation purposes)  with a prevalence on ICT of over 1% be consideredendemic and thus treated, the Malawi programme wouldinvolve 27 districts with a target population of over tenmillion. The population affected is far greater than ever envisaged. Secondly, both the northern (Karonga) andSouthern foci (the Lower Shire Valley) share internationalborders which are largely porous. This calls for innovativeapproaches in carrying out control activities as they haveto be synchronised with those in neighbouring countries. Thirdly, in some districts (Phalombe, Mulanje, Thyolo,Chikwawa and Mwanza) where LF is co-endemic withonchocercisasis the two programmes will need to bemerged. Fourthly, the LF programme will need to estab-lish links with other programmes that are delivering com-munity based interventions such as the ministry of education's deworming and feeding programme and theexpanded bed net distribution under the malaria controlprogramme. Table 2: ICT antigen prevalence data from surveys conducted in 2000 DistrictVillageNumber testedNumber positivePrevalenceLatitudeLongitude KarongaMwenitete422047.69.7125733.92973KarongaMwakyusa914448.79.6979533.89313KarongaMwenepela1025957.89.6719333.8252KarongaKashata5022449.7331533.88652KarongaMwamsaku5022449.809233.86483KarongaMwambetania5029589.8674733.86892KarongaKafikisila512345.19.9121333.93105KarongaMwenitete-mpata5024489.9495733.82237KarongaNgosi50153010.0122833.94907KarongaMwakabanga50153010.1442234.01782KarongaKanyuka511427.510.3076834.12692KarongaBonje50285610.4902734.17098NsanjeChazuka1486040.516.8426135.25259NsanjeNchacha181488658.116.6361735.17126NsanjeGamba845666.716.581135.14076ChikwawaNchingula1287659.415.9982834.48297ChikwawaZilipaine1299674.416.0799834.88262ChikwawaMbande1087670.416.1616734.79332ChikwawaPende1167968.116.0436234.72428ChikwawaBelo19615579.116.0209334.8162ChikwawaMfunde872933.316.1992935.01652ChikwawaKasokeza603456.716.1121334.92532ChikwawaKhumbulani59915.315.9923234.8791ChikwawaMuyaya782126.916.0466734.90783 Map of Malawi showing the prevalence levels recorded in the 2003 survey Figure 3 Map of Malawi showing the prevalence levels recorded in the 2003 survey.  
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